Advanced Machine Learning Engineer

6 days ago

kochi, India beBeeMloper Full time

Machine Learning Pipeline SpecialistThe role of a Machine Learning Pipeline Specialist involves designing and implementing robust ML pipelines using AWS SageMaker. This includes building, deploying, and maintaining machine learning models, as well as developing automated CI/CD workflows.Key Responsibilities:Build and deploy machine learning models using AWS SageMaker (Pipelines, Endpoints, Model Registry).Develop automated continuous integration and deployment (CI/CD) workflows using CodePipeline, CodeBuild, or GitHub Actions.Implement model monitoring, logging, and drift detection using CloudWatch and SageMaker Model Monitor.Create and maintain infrastructure using Terraform or CloudFormation.Manage secure, scalable, and cost-optimized AWS environments using IAM, VPC, and networking.Collaborate with data scientists, cloud engineers, and solution architects to ensure the successful implementation of ML pipelines.Troubleshoot issues in high-availability, production ML setups.Requirements:A minimum of 4–8 years of experience in MLOps/ML engineering.Hands-on experience with SageMaker in enterprise-scale environments.Strong Python skills and familiarity with machine learning frameworks.Experience with Docker, Kubernetes (EKS preferred), and containerization.Experience building CI/CD pipelines and automating software development processes.Deep practical knowledge of the AWS ecosystem, including services such as IAM, VPC, and CloudFormation.Nice to Have:Experience implementing model governance and ensuring compliance with security standards.Knowledge of multi-model endpoints and their application in production ML setups.Familiarity with enterprise-level security standards and compliance requirements.

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